Nemotron streaming fine-tune experimental

At a glance

Formats and quants

Hugging Face issues a DOI per repository, so each format can be cited on its own. Repositories, sizes and DOIs checked on the Hub on 2026-10-20.

Versions

Suggested implementations

The Nemotron streaming fine-tune does not have a name yet.

experimental streaming measured at 560 ms not in any app

Today it runs in NVIDIA NeMo, from the .nemo file. Offline transcription, from the model card:

import nemo.collections.asr as nemo_asr
from huggingface_hub import hf_hub_download

path = hf_hub_download(
    "Hebrish/Nemotron-Speech-Streaming-EN-0.6B-English-Hebrew-Codeswitching",
    "Nemotron-Speech-Streaming-EN-0.6B-English-Hebrew-Codeswitching.nemo",
)
model = nemo_asr.models.ASRModel.restore_from(path)
print(model.transcribe(["clip.wav"])[0].text)  # 16 kHz mono

Streaming works as for the base model, with cache-aware inference. Set att_context_size = [70, N]:

Smaller chunks mean less delay. NeMo's speech_to_text_cache_aware_streaming_infer.py example script shows the loop; see the base model card.

• Streaming accuracy, measured at 560 ms. On the held-out split (387 clips) it scored 5.65% code-switching WER while streaming, against 5.81% offline: no measurable loss, although it was fine-tuned offline with full context. The smallest chunks (80 and 160 ms) are not measured; check them for your use.
• No on-device format yet. sherpa-onnx runs NeMo cache-aware streaming transducers, so an ONNX export for sherpa-onnx is the likely route to phones and desktops. Nobody has tried it on this model yet; it is on the projects board.
• Licence: the NVIDIA Open Model License Agreement, not CC-BY-4.0. Read it before shipping. Not made or endorsed by NVIDIA.

Cite

Cite Nemotron fine-tune with its DOI, 10.57967/hf/11107 (Hebrish/Nemotron-Speech-Streaming-EN-0.6B-English-Hebrew-Codeswitching). To cite one format, use that repository's DOI from the table above.

@misc{rosehill_nemotron_2026,
  author    = {Daniel Rosehill},
  title     = {Nemotron-Speech-Streaming-EN-0.6B-English-Hebrew-Codeswitching},
  year      = {2026},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/Hebrish/Nemotron-Speech-Streaming-EN-0.6B-English-Hebrew-Codeswitching},
  doi       = {10.57967/hf/11107}
}

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